class_docstr: An auto-fitting range in a continuous scalar dimension.
  
  By default the ``start`` and ``end`` of the range automatically
  assume min and max values of the data for associated renderers.
code: def __init__(self, *args, **kwargs) -> None:
      if kwargs.get("follow") is not None:
          kwargs["bounds"] = None
      super().__init__(*args, **kwargs)
  
imports: from __future__ import annotations
  import logging
  from collections import Counter
  from math import nan
  from ..core.enums import PaddingUnits, StartEnd
  from ..core.has_props import abstract
  from ..core.properties import Auto, Bool, Datetime, Either, Enum, FactorSeq, Float, Instance, List, MinMaxBounds, Null, Nullable, Override, Readonly, Required, TimeDelta
  from ..core.validation import error
  from ..core.validation.errors import DUPLICATE_FACTORS
  from ..model import Model
label_desc: Use image node_id 1 to create a new DataRange1d object from inherited base classes: DataRange with example: obj = DataRange1d()